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Experiments of Basic Income in Worlds of Welfare

2020· book-chapter· en· W3095619542 on OpenAlexaff
Mohammad Ferdosi, Tom McDowell

Bibliographic record

VenueAdvances in finance, accounting, and economics book series · 2020
Typebook-chapter
Languageen
FieldSocial Sciences
TopicSocial Policy and Reform Studies
Canadian institutionsToronto Metropolitan UniversityMcMaster University
Fundersnot available
KeywordsWelfareBasic incomeConvergence (economics)Task (project management)EconomicsReversingPublic economicsSocial WelfarePolitical scienceEconomic growthMarket economyEngineeringLaw

Abstract

fetched live from OpenAlex

Experiments of ‘basic income' in worlds of welfare suggest that different countries are prone to experience the same pressures and moreover, in ways that lead them to produce the same socio-economic outcomes, resulting in their convergence toward an alternative social policy tool outside of their own traditional welfare models to deal with such problems. The implication is that no single welfare model has proven adequate to the task of reducing or reversing negative outcomes to any significant extent thus far. This is the most probable reason why each type of welfare regime has designed and implemented a ‘basic income' pilot in the post-2008 crisis period. However, experimental designs and results have so far diverged from each other in interesting ways, likely reflecting the interactions between different versions of ‘basic income' and the different national environments in which they have been deployed.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.882
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.013
GPT teacher head0.266
Teacher spread0.253 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designTheoretical or conceptual
Domainnot available
GenreOther

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2020
Admission routes1
Has abstractyes

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